Longitudinal Relationships of Phubbing, Depression, and Anxiety in the Middle and High School Students: A Cross‐Lagged Panel Network Analysis
Bibliographic record
Abstract
INTRODUCTION: Prior research has documented the associations among phubbing, depression, and anxiety, while the cross-sectional design failed to clarify the temporal directionality of the relationships between these mental disorders and behavioral issues. To bridge this gap, the present study utilizing longitudinal data aimed to articulate the temporal relationships between these mental disorders and behavioral issues. METHODS: = 15.17) participated in the study. Symptoms of phubbing, depression, and anxiety were assessed 18 months later (May 2023) after the baseline (November, 2021). The cross-sectional network and cross-lagged panel network models were conducted to explore the associations between the network structures of phubbing, depression, and anxiety. The network comparison test (NCT) was then performed to unveil whether the network structures vary based on school grade. RESULTS: In the cross-sectional network, significant differences in the overall structures between middle and high school students were observed. For the longitudinal network, the core symptoms responsible for temporal relationships were mostly between depressive and anxiety symptoms. Phubbing-related symptoms and restlessness (anxiety symptom) were the bridge symptoms of phubbing, depression, and anxiety. Besides, the central bridges associated with phubbing-related symptoms differed significantly across different school stages. CONCLUSIONS: Successfully regulating negative emotions can play a pivotal role in tackling the root causes linked to phubbing. Apart from addressing restlessness, future interventions focusing on nomophobia and interpersonal conflict in middle school students, as well as self-isolation in high school students, contributed to mitigating phubbing, depression, and anxiety.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".